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Record W4296498686 · doi:10.1093/pch/21.supp5.e63c

Family History-Taking in Paediatrics: It’s Much More Than Just A Checklist

2016· article· en· W4296498686 on OpenAlexaboutno aff
L Tessier, J Brehaut, B Potter, P Chakraborty, J Carroll, B Wilson

Bibliographic record

VenuePaediatrics & Child Health · 2016
Typearticle
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsnot available
Fundersnot available
KeywordsPsychosocialChecklistPsychological interventionThematic analysisPsychologyMedicineInterpersonal communicationGrounded theoryQualitative researchNursingFamily medicineMedical educationPsychiatrySocial psychology

Abstract

fetched live from OpenAlex

Abstract BACKGROUND: Family history (FH) is a risk factor for many conditions in pediatric practice; interest has increased in supporting systematic FH taking in this area by identifying core conditions for enquiry and developing point of care tools. There is little published about current practice to inform implementing such changes. OBJECTIVES: To inform future FH taking interventions by identifying pediatricians' perceptions, attitudes, beliefs, and current practices. DESIGN/METHODS: The Theoretical Domains Framework (TDF) was used to develop a comprehensive interview scheme. Semi-structured interviews were conducted with community and hospital-based pediatricians Analysis was by the constant comparison method, using a thematic approach. This study was funded by the Canadian Institutes of Health Research. RESULTS: The data revealed FH taking to be a firmly embedded, but complex aspect of pediatric practice. Participants described FH as part of regular, holistic care, extending to social and interpersonal, as well as clinical purposes; in addition to disease risk assessment, FH information helped clarify diagnosis, and select medication; tailor the overall patient management based on family circumstances; and provide psychosocial support for parents. It was also used as a method to build a relationship with parents/carers. FH and social history information were inextricably linked and often appeared to be the same concept in participants’ minds. Participating pediatricians generally expressed confidence in their FH skills and reported tailoring their approach according to experience, after initial training early in their career. While acknowledging some challenges in ensuring accuracy, they were attuned to nuances in their interactions with parents and children which would affect whether, and what, they were told about illness in the family. Most were not concerned about formal evidence, and would not change their practice except for “good reason”. CONCLUSION: The use of the TDF helped ensure a comprehensive approach to FH taking in pediatric practice. The findings suggest that FH taking in this setting is a complex activity, embedded in routine care. Recommendations for systematic enquiry about specific conditions cannot be seen as a simple additional activity to current practice. Efforts to make FH taking more systematic may founder if they fail to take into account pediatricians’ attitudes, perspectives, and practices. Further studies should explore and seek to confirm and expand our observations.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.026
metaresearch head score (Gemma)0.081
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.026
Threshold uncertainty score0.138

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0260.081
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0020.001
Scholarly communication0.0020.003
Open science0.0020.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0060.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.048
GPT teacher head0.329
Teacher spread0.281 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2016
Admission routes1
Has abstractyes

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